AI Conference 2025: Turning Intelligence into Action for the Future of PLM
San Francisco • October 2025
By the Cerebital Team
AI at the Core of the Product Lifecycle
The Cerebital team attended The AI Conference 2025 in San Francisco, a global gathering where researchers, developers, and industry leaders explored how artificial intelligence is evolving from experimentation to enterprise infrastructure.
This year’s theme was clear: operationalizing AI responsibly, efficiently, and at scale.
For Cerebital and our PLM platform, Nora IPLM, this mission resonates deeply. The discussions reinforced our vision of an AI-driven PLM ecosystem that connects design, data, and decisions into a continuous cycle of intelligence.
Table of Contents
- Agentic AI: The Rise of Digital Engineering Teammates
- Knowledge Graphs + RAG: Building the PLM Digital Brain
- Multimodal Intelligence: When AI Understands 3D
- Responsible AI: Governance as a Core Principle
- Infrastructure & Efficiency: Scaling Intelligence Sustainably
- A New Era for Product Lifecycle Intelligence
- The Road Ahead
Agentic AI: The Rise of Digital Engineering Teammates
A defining trend this year was the emergence of Agentic AI, systems capable of reasoning, planning, and acting autonomously.
These intelligent agents are moving beyond simple prompt-response patterns to orchestrate workflows, retrieve information, and support decision-making.
In PLM environments, they are evolving into digital teammates that can:
• Suggest design improvements based on historical performance and material data
• Monitor dependencies across product structures and flag risks early
• Coordinate engineering change processes automatically
At Nora IPLM, we see Agentic AI not as a replacement for engineers but as a collaborative force that accelerates innovation and enhances design intelligence.
Within PLM environments, such systems are transforming into digital teammates that can:
• Suggest design improvements based on past performance and materials data
• Monitor dependencies across product structures and flag potential risks
• Coordinate engineering change processes automatically
At Nora IPLM, Agentic AI is being developed not as a replacement for engineers, but as a collaborative force multiplier that enables faster, smarter, and more informed design cycles.
Knowledge Graphs + RAG: Building the PLM Digital Brain
Retrieval-Augmented Generation (RAG) and Knowledge Graphs were standout topics, presented as the foundation of enterprise AI.
RAG allows large language models to access live organizational knowledge, while Knowledge Graphs structure relationships between data, designs, and decisions.
Together, they form a digital brain that connects every element of product development, enabling AI to answer questions such as:
“Which past designs used the same alloy and failed under vibration testing?”
Cerebital is advancing this vision by integrating RAG and graph-based reasoning directly into Nora IPLM and creating a platform that continuously learns, adapts, and improves.
RAG allows large language models to access live organizational knowledge, while Knowledge Graphs capture structured relationships between data, designs, and decisions.
In the context of PLM, this combination forms a digital brain that connects every element of product development.
It enables AI to answer queries like:
“Which past designs used the same alloy and failed under vibration testing?”
Cerebital is advancing this vision by integrating RAG and graph-based reasoning directly into Nora IPLM, creating a platform that learns and adapts with every iteration.
Multimodal Intelligence: When AI Understands 3D
Beyond text and code, multimodal AI took center stage, showcasing how models now interpret 3D geometry, images, and documents together.
This breakthrough is critical for engineering and manufacturing, where design intent often resides within CAD models and technical drawings.
For PLM users, multimodal intelligence enables:
• Visual identification of duplicate or similar parts across assemblies
• Manufacturability assessment directly from geometric features
• Automatic generation of process plans and instructions from 3D models
These capabilities align with Cerebital’s work in spatial AI and shape-based reasoning, helping PLM systems truly “understand” the products they manage.
Responsible AI: Governance as a Core Principle
Ethics, transparency, and traceability were consistent themes throughout the conference.
As AI becomes an enterprise decision partner, governance and explainability must be integral, not optional.
For PLM systems, responsible AI means every insight should be:
• Logged and auditable
• Linked to its data sources
• Validated by human oversight when necessary
Nora IPLM is built with governance by design, embedding compliance and accountability into every layer of its intelligence framework.
In engineering, trust is the true foundation.
Infrastructure & Efficiency: Scaling Intelligence Sustainably
Another focus area was AI infrastructure. The conversation is shifting from ever-larger models toward smaller, specialized systems that are faster, more secure, and cost-effective.
For enterprise PLM, this translates to:
• Faster inference through optimized models
• Hybrid or on-premises deployments to safeguard IP
• Scalable architectures balancing performance and privacy
Cerebital is building toward this future by delivering lightweight, high-performance AI that scales with the customer’s data, not against it.
A New Era for Product Lifecycle Intelligence
The conversations in the conference reaffirmed what we have been building toward: AI is no longer experimental; it is essential.
For PLM, this shift transforms the platform from a static repository into a living, learning system that predicts, collaborates, and evolves with every decision.
Through Nora IPLM, Cerebital is leading this transformation, where AI agents think with data, knowledge graphs connect enterprise context, and multimodal intelligence brings design understanding to life.
The Road Ahead
AI is not replacing creativity; it is amplifying it.
The next generation of PLM will be measured not only by how it manages information but by how intelligently it learns from it.
At Cerebital, we are building that future today by turning product lifecycle management into product intelligence management.
Innovation Meets Product Lifecycle Management
Discover how IPLM empowers teams to manage issues and risks effectively, keeping product development on track.
Frequently Asked Questions
Cloud PLM is a product lifecycle management system hosted in the cloud. It allows SMBs to manage product data, BOMs, documents, and workflows without complex IT infrastructure.
SMBs face challenges like scattered CAD files, spreadsheet errors, and version control problems. Cloud PLM offers collaboration, faster development, and scalability.
Benefits include fewer errors, faster product development cycles, lower costs, better collaboration, and the ability to compete with larger enterprises.
Look for platforms that are easy to use, offer transparent pricing, integrate with CAD tools, and provide responsive support. Nora IPLM meets these requirements for SMBs.
Yes. Modern cloud PLM platforms connect with CAD software, project management tools, and document repositories to streamline workflows.
Cloud PLM tracks changes, enforces access permissions, and maintains an audit trail for quality and regulatory compliance.
Platforms like Nora IPLM offer dedicated support, documentation, and live demos to ensure smooth adoption.
Explore More from Nora IPLM
Discover more ways Nora IPLM simplifies product development and innovation. Explore related topics, use cases, and platform features that help your teams work smarter and bring better products to market faster.
Explore Our All Features
Nora IPLM connects people, processes, and systems to streamline product development with a highly customizable interface.
Product Lifecycle Management
Efficiently manage, collaborate, and innovate across every stage of your product lifecycle.
Revolutionizing BOM Management
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